40 citations · 85 across the 23 of their papers we have counts for
12 papers · 1 filter
Lhotse: a speech data representation library for the modern deep learning ecosystem
Piotr Żelasko, Daniel Povey, Jan "Yenda" Trmal +1
Speech data is notoriously difficult to work with due to a variety of codecs, lengths of recordings, and meta-data formats. We present Lhotse, a speech data representation library…
Unsupervised Speech Segmentation and Variable Rate Representation Learning using Segmental Contrastive Predictive Coding
Saurabhchand Bhati, Jesús Villalba, Piotr Żelasko +2
Typically, unsupervised segmentation of speech into the phone and word-like units are treated as separate tasks and are often done via different methods which do not fully leverage…
Beyond Isolated Utterances: Conversational Emotion Recognition
Raghavendra Pappagari, Piotr Żelasko, Jesús Villalba +2
Speech emotion recognition is the task of recognizing the speaker's emotional state given a recording of their utterance. While most of the current approaches focus on inferring em…
Joint prediction of truecasing and punctuation for conversational speech in low-resource scenarios
Raghavendra Pappagari, Piotr Żelasko, Agnieszka Mikołajczyk +2
Capitalization and punctuation are important cues for comprehending written texts and conversational transcripts. Yet, many ASR systems do not produce punctuated and case-formatted…
Representation Learning to Classify and Detect Adversarial Attacks against Speaker and Speech Recognition Systems
Jesús Villalba, Sonal Joshi, Piotr Żelasko +1
Adversarial attacks have become a major threat for machine learning applications. There is a growing interest in studying these attacks in the audio domain, e.g, speech and speaker…
What Helps Transformers Recognize Conversational Structure? Importance of Context, Punctuation, and Labels in Dialog Act Recognition
Piotr Żelasko, Raghavendra Pappagari, Najim Dehak
Dialog acts can be interpreted as the atomic units of a conversation, more fine-grained than utterances, characterized by a specific communicative function. The ability to structur…
Segmental Contrastive Predictive Coding for Unsupervised Word Segmentation
Saurabhchand Bhati, Jesús Villalba, Piotr Żelasko +2
Automatic detection of phoneme or word-like units is one of the core objectives in zero-resource speech processing. Recent attempts employ self-supervised training methods, such as…
Deep Feature CycleGANs: Speaker Identity Preserving Non-parallel Microphone-Telephone Domain Adaptation for Speaker Verification
Saurabh Kataria, Jesús Villalba, Piotr Żelasko +2
With the increase in the availability of speech from varied domains, it is imperative to use such out-of-domain data to improve existing speech systems. Domain adaptation is a prom…
Earnings-21: A Practical Benchmark for ASR in the Wild
Miguel Del Rio, Natalie Delworth, Ryan Westerman +7
Commonly used speech corpora inadequately challenge academic and commercial ASR systems. In particular, speech corpora lack metadata needed for detailed analysis and WER measuremen…
Unsupervised Acoustic Unit Discovery by Leveraging a Language-Independent Subword Discriminative Feature Representation
Siyuan Feng, Piotr Żelasko, Laureano Moro-Velázquez +1
This paper tackles automatically discovering phone-like acoustic units (AUD) from unlabeled speech data. Past studies usually proposed single-step approaches. We propose a two-stag…
Adversarial Attacks and Defenses for Speech Recognition Systems
Piotr Żelasko, Sonal Joshi, Yiwen Shao +4
The ubiquitous presence of machine learning systems in our lives necessitates research into their vulnerabilities and appropriate countermeasures. In particular, we investigate the…
Study of Pre-processing Defenses against Adversarial Attacks on State-of-the-art Speaker Recognition Systems
Sonal Joshi, Jesús Villalba, Piotr Żelasko +2
Adversarial examples to speaker recognition (SR) systems are generated by adding a carefully crafted noise to the speech signal to make the system fail while being imperceptible to…